A survey reviewing benchmark data contamination in LLMs, its impact on evaluation, and alternative assessment approaches.
Sentiment analysis algorithms and applications: A survey
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DistilBERT achieves 84.78% accuracy and 84.75% F1-score on binary sentiment classification of Indonesian student opinions about AI in higher education, outperforming SVM at 82.14%.
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Benchmark Data Contamination of Large Language Models: A Survey
A survey reviewing benchmark data contamination in LLMs, its impact on evaluation, and alternative assessment approaches.